Autophagy regulates exosomal release of prions in neuronal cells
Bibliographic record
Abstract
Prions are protein-based infectious agents that autocatalytically convert the cellular prion protein PrP C to its pathological isoform PrP Sc . Subsequent aggregation and accumulation of PrP Sc in nervous tissues causes several invariably fatal neurodegenerative diseases in humans and animals. Prions can infect recipient cells when packaged into endosome-derived nanoparticles called exosomes, which are present in biological fluids such as blood, urine, and saliva. Autophagy is a basic cellular degradation and recycling machinery that also affects exosomal processing, but whether autophagy controls release of prions in exosomes is unclear. Our work investigated the effect of autophagy modulation on exosomal release of prions and how this interplay affects cellular prion infection. Exosomes isolated from cultured murine central neuronal cells (CAD5) and peripheral neuronal cells (N2a) contained prions as shown by immunoblotting for PrP Sc , prion-conversion activity, and cell culture infection. We observed that autophagy stimulation with the mTOR inhibitor rapamycin strongly inhibited exosomal prion release. In contrast, inhibition of autophagy by wortmannin or CRISPR/Cas9-mediated knockout of the autophagy protein Atg5 (autophagy-related 5) greatly increased the release of exosomes and exosome-associated prions. We also show that a difference in exosomal prion release between CAD5 and N2a cells is related to differences at the level of basal autophagy. Taken together, our results indicate that autophagy modulation can control lateral transfer of prions by interfering with their exosomal release. We describe a novel role of autophagy in the prion life cycle, an understanding that may provide useful targets for containing prion diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".